Signal-Based Medium Analysis

ABSTRACT

A solution for evaluating a medium using electrical signals is described. A plurality of electrical signals having different frequencies are transmitted through the medium and signal data corresponding to the electrical signals after having traveled through the medium is acquired. A complex impedance and a complex permittivity and/or complex conductivity can be calculated for the medium. A set of characteristics of the medium can be computed using mixing models and/or known information of the medium. A level of one or more attributes of the medium can be determined from the characteristics using nonparametric Bayesian inference. One particular application is directed to determining a nitrate level of soil.

REFERENCE TO RELATED APPLICATIONS

The current application is a continuation of U.S. Pat. ApplicationSerial No. 17/567,797, filed on 3 Jan. 2022, which is a continuation ofU.S. Pat. Application Serial No. 16/652,237, filed on 30 Mar. 2020,which is a U.S. National Phase application of International ApplicationNo. PCT/US2018/054316, filed on 4 Oct. 2018, which claims the benefit ofU.S. Provisional Application No. 62/567,885, filed on 4 Oct. 2017, allof which are hereby incorporated by reference.

TECHNICAL FIELD

The disclosure relates generally to analysis of a medium usingelectrical signals, and more particularly, to a solution for measuringvarious characteristics of the medium from signal data for multiplefrequencies transmitted through the medium.

BACKGROUND ART

There are numerous economic and environmental issues related to soil andwater management. A broad societal economic issue is that as thepopulation continues to increase, crop yield becomes more important. Forinstance, from 1962 to 2000, the amount of land used around the worldfor crop production increased by 13%, while the world populationincreased by 89%.

These issues increase the need to better understand the role ofparticular nutrients, such as nitrogen, in crop production. Nitrogenrich fertilizer has contributed an estimated 40% to the increase inper-capita food production in the past 50 years. In addition, theproductivity and efficiency of the land and a crop’s growth and qualityhave a direct relationship to the cost of those goods to the consumer,even if the full effect takes 10 to 12 months to move through the retailfood chain.

Profitability of farmed crops can be severely negatively impacted ifpoor nitrogen management practices are used. One of the limitations isthe inability to assess soil and plant data rapidly and inexpensively inthe field. A key component and barrier is the lack of a soilnitrate-nitrogen measurement system. Hence, much research continues tofocus on the development of instrumentation to help in the precisionagriculture (PA) decision-making process by measuring different soilattributes within a field.

Soil nitrogen is often deficient, despite the fact that it is anessential nutrient for optimal crop production. When soil nitrogen istoo abundant and exceeds a crop’s requirements, there is a greaterlikelihood of negative environmental impacts such as leaching,denitrification, and volatilization. Nitrogen in the soil also can belost through crop removal, soil erosion, and runoff. By monitoringimportant soil characteristics (e.g., nitrate levels and moisture) inmultiple locations over a field of interest, the development of a waterand fertilizer plan can be adapted more easily to changing environmentalconditions and crop needs. This effort results in substantial positiveenvironmental and economic returns for farmers.

The amount of fertilizer necessary varies with the crop to be grown, thedesired yield, the amount of nutrients (e.g., nitrogen) already presentin the soil, and the region in which the crops are grown. Therefore, itis common practice to base fertilizer application amounts on localknowledge and expertise. For corn, it is common to measure the soilnitrates using a Pre-sidedress Nitrate Test (PSNT), which is anin-season soil nitrate test that is done to determine if additionalnitrogen rich fertilizer is needed to reach optimal yield. To completethis test, 12-inch soil cores are taken from the field, usually one ortwo cores per acre due to the time and effort involved. The soil samplesare processed quickly to stop the microbe activity and the compositefield sample is mailed to a laboratory to measure the nitrate levelusing a spectrophotometric meter. The sampling, processing, mailing, andanalyzing process may take 48 hours. If a field soil test kit with acommercial handheld meter or test strips is used, the sampling,processing, and testing still can take 24 hours.

Depending on the relative uniformity of the field with respect to soilcharacteristic, different corn strands, management history, etc., thesample area size can vary from 1 to 10 acres or more. In other soilsampling strategies, it is common to collect 15 to 30 soil cores atdepths varying from six inches to two feet to represent 10 to 20 acres,assuming a uniform field. As with the PSNT, the samples need to beprocessed for the nitrate measurement with the same labor intensive andtime-consuming efforts.

SUMMARY OF THE INVENTION

Aspects of the invention provide a solution for evaluating a mediumusing electrical signals. A plurality of electrical signals havingdifferent frequencies are transmitted through the medium and signal datacorresponding to the electrical signals after having traveled throughthe medium is acquired. A complex impedance and a complex permittivityand/or a complex conductivity can be calculated for the medium. A set ofcharacteristics of the medium can be computed using mixing models and/orknown information of the medium. A level of one or more attributes ofthe medium can be determined from the characteristics usingnonparametric Bayesian inference.

One illustrative application is directed to determining a nitrate levelof soil. To this extent, an embodiment provides a field in-situinstrument that can measure soil nutrient content, such as a nitrateconcentration, in real-time. The results provided by the instrument canaid in the decision-making process for developing an effective cropgrowth strategy. Additionally, the instrument can add to the collectionof tools used in precision agriculture (PA), where optimizing returnswhile preserving resources is an important goal. To this extent, theinstrument can help improve agricultural soil health, thereby improvingan effectiveness of farmers and agriculture professionals with theirland and other resources, while maintaining optimum crop yield andproduction efficiency. Providing real-time information can allow forfield plans to be developed or adapted to conditions more quickly andeasily by farmers and land managers. In addition, such information canprovide an easier way to do more localized testing of soil conditionswith greater ease, thereby further reducing the negative environmentaland economic effects of harmful and damaging over fertilization.

A first aspect of the invention provides a system comprising: a computersystem including means for evaluating a medium, the means for evaluatingincluding: obtaining signal data corresponding to a plurality ofelectrical signals having traveled through the medium, each of theplurality of electrical signals having a different frequency; measuringa complex impedance of the medium using the signal data; computing atleast one of: a complex permittivity or a complex conductivity, usingthe complex impedance and an electrode model corresponding to aconfiguration of electrodes used to acquire the signal data; computing aset of characteristics of the medium using the at least one of: thecomplex permittivity or the complex conductivity, and a set of mixingmodels, wherein each characteristic in the set of characteristics has atleast one corresponding mixing model in the set of mixing models; andproviding the set of characteristics for use in evaluating the medium.

An embodiment of the system can include a conducting electrode fortransmitting the electrical signals and a set of probe electrodes foracquiring the signal data corresponding to the electrical signals afterpassing through the medium. The computer system can operate theconducting electrode to transmit each of the signals into the medium andreceive the signal data from the set of probe electrodes located in themedium. In a more particular embodiment, each probe electrode includes apair of guard electrodes located on opposing sides of a guardedelectrode. An embodiment of the set of probe electrodes can include atleast two probe electrodes, with each of the probe electrodes located aknown distance from the conducting electrode and at a known positionrelative to each of the other probe electrodes.

The computer system can obtain known information regarding the mediumfrom one or more sources of information, such as a user, a previoustest, an external data source, etc. The known information can be used inone or more of various stages of processing the signal data. Forexample, known information can be used in conjunction with a set ofcharacteristics for the medium to determine at least one attributelevel.

The computer system can implement various models and approaches fordetermining the characteristic(s) and/or attribute level(s) of themedium. The computer system can use an electrode model to remove aneffect of the electrode configuration from the signal data. Anembodiment of the electrode model corresponds to a transmission linemodel. One or more attribute levels of the medium can be determinedusing a nonparametric Bayesian inference solution.

In an illustrative embodiment described herein, the medium comprisessoil, such as agricultural soil. An embodiment of a system can provide aportable solution for evaluating the soil in situ and obtainingmeasurements of one or more characteristics of the soil and/or attributelevels of the soil in real time. The characteristics can include a watercontent of the soil and an attribute level can include a nitrate levelof the soil. The results of the evaluation can be provided for use inmanaging one or more aspects of the soil, such as determining and/ormodifying a watering schedule, a fertilization schedule, etc.

A second aspect of the invention provides a method of evaluating amedium, the method comprising: obtaining signal data corresponding to aplurality of electrical signals having traveled through the medium on acomputer system, each of the plurality of electrical signals having adifferent frequency; the computer system measuring a complex impedanceof the medium using the signal data; the computer system computing atleast one of: a complex permittivity or a complex conductivity, usingthe complex impedance and an electrode model corresponding to aconfiguration of electrodes used to acquire the signal data; thecomputer system computing a set of characteristics of the medium usingthe at least one of: the complex permittivity or the complexconductivity, and a set of mixing models, wherein each characteristic inthe set of characteristics has at least one corresponding mixing modelin the set of mixing models; and the computer system providing the setof characteristics for use in evaluating the medium.

A third aspect of the invention provides a portable soil evaluationsystem comprising: an electrode component including: a conductingelectrode for transmitting a plurality of electrical signals; and a setof probe electrodes for acquiring signal data corresponding to theplurality of electrical signals after passing through soil; and acomputer system including means for evaluating the soil, the means forevaluating including: operating the electrode component to emit aplurality of electrical signals from the conducting electrode andacquire signal data from at least one of the set of probe electrodescorresponding to the plurality of electrical signals having traveledthrough the soil, each of the plurality of electrical signals having adifferent frequency; measuring a complex impedance of the soil using thesignal data; computing at least one of: a complex permittivity or acomplex conductivity, using the complex impedance and an electrode modelcorresponding to a configuration of the conducting electrode and the setof probe electrodes used to acquire the signal data; computing a set ofcharacteristics of the medium using the at least one of: the complexpermittivity or the complex conductivity, and a set of mixing models,wherein each characteristic in the set of characteristics has at leastone corresponding mixing model in the set of mixing models; determiningat least one attribute level in the soil using known information of thesoil and at least one of the set of characteristics for the soil; andpresenting the at least one attribute level to the user in real time.

The illustrative aspects of the invention are designed to solve one ormore of the problems herein described and/or one or more other problemsnot discussed.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other features of the disclosure will be more readilyunderstood from the following detailed description of the variousaspects of the invention taken in conjunction with the accompanyingdrawings that depict various aspects of the invention.

FIG. 1 shows an illustrative environment for analyzing soil according toan embodiment.

FIGS. 2A and 2B show perspective and top views, respectively, of anillustrative electrode component according to an embodiment.

FIGS. 3A and 3B show an illustrative conducting electrode structure andprobe electrode structure according to embodiments.

FIG. 4 shows an illustrative process for measuring one or moreattributes of a medium according to an embodiment.

It is noted that the drawings may not be to scale. The drawings areintended to depict only typical aspects of the invention, and thereforeshould not be considered as limiting the scope of the invention. In thedrawings, like numbering represents like elements between the drawings.

DETAILED DESCRIPTION OF THE INVENTION

Aspects of the invention provide a solution for evaluating a mediumusing electrical signals. A plurality of electrical signals havingdifferent frequencies are transmitted through the medium and signal datacorresponding to the electrical signals after having traveled throughthe medium is acquired. A complex impedance and a complex permittivityand/or complex conductivity can be calculated for the medium. A set ofcharacteristics of the medium can be computed using mixing models and/orknown information of the medium. A level of one or more attributes ofthe medium can be determined from the characteristics usingnonparametric Bayesian inference.

In an illustrative application of the invention used to illustratevarious aspects of the invention, a solution for analyzing one or moreaspects of soil nutrient content is described. Embodiments can performthe analysis of the soil in-situ, thereby not requiring the acquisitionand processing of soil samples for testing. In an illustrativeembodiment, a solution for analyzing the nitrate concentration inagricultural soil is described. However, it is understood that nitrateconcentration is only illustrative of the soil nutrient analysis thatcan be performed in embodiments. Additionally, agricultural soil is alsoonly illustrative of the types of soil that can be analyzed using asolution described herein. Still further, soil is only illustrative ofvarious types of media that can be analyzed using a solution describedherein.

Turning to the drawings, FIG. 1 shows an illustrative environment 10 foranalyzing soil according to an embodiment. To this extent, theenvironment 10 includes a computer system 20 that can perform a processdescribed herein in order to analyze one or more aspects of soil 4. Inparticular, the computer system 20 is shown including an analysisprogram 30, which makes the computer system 20 operable to analyze thesoil 4 by performing a process described herein.

The computer system 20 is shown including a processing component 22(e.g., one or more processors), a storage component 24 (e.g., a storagehierarchy), an input/output (I/O) component 26 (e.g., one or more I/Ointerfaces and/or devices), and a communications pathway 28. In general,the processing component 22 executes program code, such as the analysisprogram 30, which is at least partially fixed in storage component 24.While executing program code, the processing component 22 can processdata, which can result in reading and/or writing transformed datafrom/to the storage component 24 and/or the I/O component 26 for furtherprocessing. The pathway 28 provides a communications link between eachof the components in the computer system 20.

The I/O component 26 can enable the computer system 20 to communicatedirectly with a human and/or one or more other components or systems. Tothis extent, the I/O component 26 can comprise one or more human I/Odevices, which enable a human user 12 to interact with the computersystem 20 and/or one or more communications devices to enable a systemuser 12, another component of the system (e.g., an electrode component14), an external data source 33, and/or the like, to communicate withthe computer system 20 using any combination of one or more of varioustypes of communications links. To this extent, the analysis program 30can manage a set of interfaces (e.g., graphical user interface(s),application program interface, and/or the like) that enable human and/orsystem users 12 to interact with the computer system 20. Furthermore,the analysis program 30 can manage (e.g., store, retrieve, create,manipulate, organize, present, etc.) the data, such as soil data 34,using any solution.

In any event, the computer system 20 can comprise one or more generalpurpose computing articles of manufacture (e.g., computing devices)capable of executing program code, such as the analysis program 30,installed thereon. As used herein, it is understood that “program code”means any collection of instructions, in any language, code or notation,that cause a computing device having an information processingcapability to perform a particular action either directly or after anycombination of the following: (a) conversion to another language, codeor notation; (b) reproduction in a different material form; and/or (c)decompression. To this extent, the analysis program 30 can be embodiedas any combination of system software and/or application software.

Furthermore, the analysis program 30 can be implemented using a set ofmodules 32. In this case, a module 32 can enable the computer system 20to perform a set of tasks used by the analysis program 30, and can beseparately developed and/or implemented apart from other portions of theanalysis program 30. As used herein, the term “component” means anyconfiguration of hardware, with or without software, which implementsthe functionality described in conjunction therewith using any solution,while the term “module” means program code that enables a computersystem 20 to implement the actions described in conjunction therewithusing any solution. When fixed in a storage component 24 of a computersystem 20 that includes a processing component 22, a module is asubstantial portion of a component that implements the actions.Regardless, it is understood that two or more components, modules,and/or systems may share some/all of their respective hardware and/orsoftware. Furthermore, it is understood that some of the functionalitydiscussed herein may not be implemented or additional functionality maybe included as part of the computer system 20.

When the computer system 20 comprises multiple computing devices, eachcomputing device can have only a portion of the analysis program 30fixed thereon (e.g., one or more modules 32). However, it is understoodthat the computer system 20 and the analysis program 30 are onlyrepresentative of various possible equivalent computer systems that mayperform a process described herein. To this extent, in otherembodiments, the functionality provided by the computer system 20 andthe analysis program 30 can be at least partially implemented by one ormore computing devices that include any combination of general and/orspecific purpose hardware with or without program code. In eachembodiment, the hardware and program code, if included, can be createdusing standard engineering and programming techniques, respectively.

Regardless, when the computer system 20 includes multiple computingdevices, the computing devices can communicate over any type ofcommunications link. Furthermore, while performing a process describedherein, the computer system 20 can communicate with one or more othercomputer systems and/or components (such as the electrode component 14and/or the external data source 33) of a system described herein usingany type of communications link. In either case, the communications linkcan comprise any combination of various types of optical fiber, wired,and/or wireless links; comprise any combination of one or more types ofnetworks; and/or utilize any combination of various types oftransmission techniques and protocols.

As discussed herein, the analysis program 30 enables the computer system20 to analyze a medium, such as soil 4. To this extent, the computersystem 20 can receive soil data 34 from a electrode component 14 whichis located at a desired location below ground 2, in the soil 4. Thecomputer system 20 (e.g., as directed by the analysis program 30) canoperate the electrode component 14 and/or process the soil data 34 andgenerate additional soil data 34 therefrom. The computer system 20 canevaluate the additional soil data 34 to determine one or morecharacteristics and/or attributes of interest of the soil. The computersystem 20 also can obtain data relevant to the evaluation from one ormore external data sources 33. Illustrative external data sources 33 caninclude a soil management system used to manage the soil 4, a governmentdatabase, and/or the like. Information that can be obtained from theexternal data source(s) 33 can include data corresponding to: a previousevaluation of the soil 4; a previous treatment applied to the soil 4;recent weather for an area in which the soil 4 is located; soil surveyinformation; etc.

In an embodiment, the environment 10 is configured to provide a portablesolution for analyzing one or more attributes of the soil 4 in realtime. To this extent, the computer system 20 and the electrode component14 can be configured to be portable by a single person, rugged, and easyto use. The electrode component 14 can include electrodes, which can beindividually replaced should one become damaged, or in the event that adifferent depth of measurement is desired. The electrode component 14can be configured to facilitate locating multiple electrodes in the soil4 with a known arrangement. For example, the electrode component 14 caninclude a conducting electrode and one or more probe electrodes. Theelectrode component 14 can enable placement of the electrodes in thesoil 4 such that each probe electrode is a known distance from theconducting electrode and is located at a known position relative to eachof the other probe electrode(s). As used herein, a distance is knownwhen it is sufficiently accurate for the corresponding calculations tohave a desired accuracy. In a more particular embodiment, the distanceis accurate to within +/- 5 millimeters. Additionally, as used herein arelative position of two probe electrodes is known when an angle formedby the two probe electrodes with the conducting electrode at a vertex isknown to an accuracy sufficient for the corresponding calculations tohave a desired accuracy. In a more particular embodiment, the angle isaccurate to within +/- 5 degrees.

FIGS. 2A and 2B show perspective and top views, respectively, of anillustrative electrode component 14 according to an embodiment. In thiscase, the electrode component 14 comprises five electrode structures 40,42A-42D. A conducting electrode structure 40 can be surrounded by fourprobe electrode structures 42A, 42D, each of which can be located atsubstantially the same distance from the conducting electrode structure40 and spaced evenly (e.g., arranged 90°) from each other. Asillustrated in FIG. 2B, the actual distance between the conductingelectrode structure 40 and each of the probe electrode structures42A-42D can vary. For example, the electrode component 14 can bepre-configured and/or include a template or guide that enables a user toselectively install the probe electrode structures 42A-42D at any of aplurality of distances from the conducting electrode structure 40.Regardless, it is understood that the distance must be known so thatproper calculations can be performed as described herein.

While all of the probe electrode structures 42A-42D are shown as beinglocated the same distance from the conducting electrode structure 40, itis understood that this configuration is only illustrative. In anembodiment, the distances between the conducting electrode structure 40and the probe electrode structures 42A-42D vary. Regardless, thedistance between each probe electrode structure 42A-42D and theconducting electrode structure 40 must be known to an accuracysufficient for the models. In an embodiment, the computer system 20(FIG. 1 ) can specify a configuration for placement of the probeelectrode structures 42A-42D based on one or more prior known conditionsof the soil. For example, the computer system 20 can specify that twoprobe electrodes (e.g., located across from each other) be located at afirst distance from the conducting electrode structure 40 while twoprobe electrodes are specified to be located at a second, differentdistance from the conducting electrode structure 40. The distance(s)between the conducting electrode structure 40 and each of the probeelectrode structures 42A-42D can be in any range of distances. In anembodiment, the distance(s) are at least 20 millimeters. In a moreparticular embodiment, the distances are in a range between 20millimeters and 20 centimeters.

An embodiment of the electrode component 14 can include one or morecomponents to facilitate proper and accurate placement of the electrodestructures 40, 42A-42D within the soil. In an embodiment, the electrodecomponent 14 is configured to secure an end of each of the electrodestructures 40, 42A-42D at a particular location and in a particularorientation on a member 44A. For example, the member 44A can include amechanism for securing an end of each of the electrode structures 40,42A-42D to the member 44A such that the electrode structures 40, 42A-42Dwill remain in substantially the same arrangement while the electrodecomponent 14 is inserted into the soil. In an embodiment, the mechanismfor an electrode includes a threaded opening in the member 44A intowhich a threaded end of the electrode can be inserted. In an embodiment,an electrode is connected to the member 44A using a radio frequencyconnector, such as a Bayonet Neill-Concelman (BNC) connector, which alsocan connect each electrode structure 40, 42A-42D to the computer system20.

In an embodiment, the member 44A is configured to secure each electrodestructure 40, 42A-42D while allowing the user 12 access to a radiofrequency connector for each electrode structure 40, 42A-42D. Forexample, the connector can be located on a top of each electrode and themember 44A can include an opening that allows access to the connectorfrom a top side of the member 44A. In this configuration, the user 12can disconnect the electrode structures 40, 42A-42D from the computersystem 20 during insertion, removal, and/or transport of the electrodecomponent 14.

In an embodiment, the electrode component 14 can include a templatemember 44B for facilitating placement of the electrodes in the properposition and/or orientation within the soil. For example, the templatemember 44B can include openings corresponding to possible configurationsfor placement of the electrode structures 40, 42A-42D. Each opening canbe sized to allow the electrode structure 40, 42A-42D to be insertedthere through while also restricting lateral movement of the electrodestructure 40, 42A-42D, e.g., due to deflection from the presence of astone or the like. To this extent, the template member 44B also can havea thickness sufficient to restrict such lateral movement.

Each member 44A, 44B can be formed of any suitable material. Forexample, the member 44A can be fabricated from a non-conducting materialhaving sufficient strength to allow insertion of the electrode structure40, 42A-42D into the soil by, for example, pushing down and/or poundingon a top surface of the member 44A without deforming the member 44A. Inan embodiment, the electrode structures 40, 42A-42D can be individuallyinserted into the soil. In this case, the electrode component 14 can beimplemented without the member 44A. The member 44B can be used as atemplate for inserting each electrode structure 40, 42A-42D and can beformed of a material having sufficient strength to withstand inadvertentpounding during insertion of the electrode structures 40, 42A-42D. Useof one or both members 44A, 44B can assist in aligning the electrodestructures 40, 42A-42D such that the corresponding electrodes aresubstantially aligned. Known alignment of the electrodes can reduceerrors in the model calculations.

It is understood that insertion of the electrode structures 40, 42A-42Dinto the soil is only illustrative of various approaches for surroundingthe electrode structures 40, 42A-42D with a soil to be tested. Forexample, in an embodiment, soil can be placed within a container and theelectrode component 14 can be inserted therein. Alternatively, theelectrode component 14 can comprise a container with the electrodestructures 40, 42A-42D mounted therein and the soil can be inserted inthe container surrounding the electrodes. Still further, a hole can bedug in the ground into which the electrode component 14 is placed andsubsequently surrounded with soil. In this case, one or both members44A, 44B an include openings (e.g., a screen and/or large scaleopenings) to allow soil to pass there through and effectively surroundthe electrode structures 40, 42A-42D. Such placement approaches can beused, for example, when the soil includes a lot of stones, which canpreclude accurate placement and orientation of the electrode structures40, 42A-42D.

One or more of the electrode structures 40, 42A-42D can be designed andconstructed to eliminate electric field fringing effects at the edges ofthe electrodes. To this extent, FIGS. 3A and 3B show an illustrativeconducting electrode structure 40 and probe electrode structure 42according to embodiments. The conducting electrode structure 40 cancomprise a conducting electrode 50, while the probe electrode structure42 includes a probe electrode 52, which includes guard electrodes 54A,54B located on opposing sides of a guarded electrode 53. In a moreparticular embodiment, both electrodes 50, 52 have substantially thesame diameters (e.g., approximately 13.7 mm in an illustrativeembodiment). The conducting electrode 50 can have a length ofapproximately 150 mm. The probe electrode 52 also can have an overalllength of approximately 150 mm, and include a guarded electrode 53having a length of approximately 100 mm, with each guard electrode 54A,54B having a length of approximately 20 mm. A space 56A, 56B can belocated between the guarded electrode 53 and each guard electrode 54A,54B of approximately 5 mm.

It is understood that the various dimensions for the electrodes 50, 52are only illustrative. To this extent, embodiments of an electrode canhave any diameter suitable for use in conjunction with the correspondingmodel(s) and measurement frequencies. In general, smaller diameters canmake insertion of the electrode structures 40, 42 into the soil easier.In an embodiment, the electrodes 50, 52 have diameters in a rangebetween approximately five millimeters and approximately twentymillimeters. Similarly, the heights of the electrodes 50, 52 can be thesame or vary. In an embodiment, the electrodes 50, 52 have overallheights in a range between approximately 5 centimeters and 30centimeters. Furthermore, it is understood that the correspondingelectrode structures 40, 42 can have differing dimensions (e.g.,diameters and/or heights). Regardless, the dimensions of each electrode50, 52 must be known to a sufficient accuracy for use in thecorresponding model(s).

While only a single probe electrode structure 42 is shown in FIG. 3B, itis understood that each of the probe electrode structures 42A-42D can beconstructed in the same manner as the probe electrode structure 42 shownin FIG. 3B. However, it is understood that a probe electrode 52 can bedesigned and constructed as an unguarded electrode, e.g., similar to theconducting electrode 50. As the electrode structures 40, 42 may beutilized in environments including water, the electrode structures 40,42 can be constructed to be liquid tight. Additionally, each electrodestructure 40, 42 can have a narrowed, pointed end 58 that can facilitateinserting the electrode structure 40, 42 into the soil with the end 58pointed down. In an embodiment, the electrode structures 40, 42 have atop portion that is configured to facilitate placement of thecorresponding electrodes 50, 52 at a desired depth within the soil.However, it is understood that the electrodes can have any orientationwithin the soil.

Each of the electrodes 50, 53, 54A, 54B can be fabricated from anysuitable conductive material, such as copper, aluminum, and/or the like.The pointed end 58 can be fabricated of a rugged material, such assteel, to facilitate insertion into the soil. The remaining structure ofeach electrode structure 40, 42 can be formed of any suitablenon-conductive material, such as plastic, rubber, and/or the like.Regardless, the structure of each component of the electrode structures40, 42 can be configured to withstand the forces required to insert theelectrode structures 40, 42 into the soil.

FIG. 4 shows an illustrative process for measuring one or moreattributes of a medium, such as soil 4, which can be implemented by theenvironment 10. Referring to FIGS. 1-4 , the user 12 can position and/orconfigure the electrode component 14 in a desired location within thesoil 4 using any solution. For example, as discussed herein, the user 12can insert the electrodes into the soil 4 individually (e.g., using atemplate) or collectively. Additionally, the user 12 can place soil 4around the electrode component 14, e.g., in a container, in a hole inthe ground 2, and/or the like.

In an embodiment, the environment 10 can provide an analysis solutionthat is self-calibrating. For example, the computer system 20 can beconfigured to self-determine what electrode pattern(s) and/orplacement(s) are necessary to obtain the most accurate soil measurementsfor use in the soil models. To self-calibrate, the computer system 20can use prior knowledge regarding the soil 2, which can be acquired fromthe user 12, from an external data source 33, such as the USDA soilsurvey app (e.g., soil texture, parent material information), from anexternal lab, and/or the like. In an embodiment, the computer system 20can acquire a set of initial impedance measurements after placement ofthe electrode component 14 in the soil 4 to determine which of theactive electrodes in the electrode component 14 will be used to take themeasurements. Within the initial data set taken for the self-calibrationprocess, the computer system 20 can analyze various data attributes,such as the signal-to-noise ratio, minimum resolution, and/or the like.As long as the measurements meet the model(s) requirements, the activeelectrode configuration(s) can be utilized. If the computer system 20determines that none of the electrode patterns provides information thatis useful for the models, the computer system 20 can prompt the user 12to change the placement of the electrode component 14 in the soil 4, theelectrode configuration for the electrode component 14, and/or the like.

Once positioned at a desired location and in a configuration suitablefor acquiring measurement data of sufficient quality, the computersystem 20 can emit electrical signals from the conducting electrodestructure 40, which are subsequently detected by one or more of theprobe electrode structures 42A-42D after traveling through the soil 4.To this extent, in action A12, the computer system 20 can emit anelectrical signal having a predetermined frequency into the soil 4 fromthe conducting electrode 50 and in action A14, the computer system 20can acquire electrical signal data using one or more of the probeelectrodes 52 corresponding to the electrical signal after havingtraveled through and interacted with the soil 4. The electrical signaldata can include, for example, a voltage magnitude and phase, a currentmagnitude and phase, etc., for the corresponding frequency.Additionally, the computer system 20 can store data corresponding to oneor more electrical properties of the electrode component 14 which arenot dependent on the electrical signals, such as resistance. In actionA16, the computer system 20 can determine whether the process requiresanother electrical signal to be transmitted at another frequency. If so,the process can return to action A12.

In an embodiment, the process includes generation of multiple electricalsignals, each of a different frequency, over a range of frequencies. Inan embodiment, the range of frequencies includes radio frequencies. Therange of frequencies can be selected based on one or more knownattributes of the soil, which can be provided by the user 12, acquiredfrom an external data source 33, and/or the like. In a more particularembodiment, an illustrative process can generate and detect electricalsignals of frequencies in a range between 10 kHz and 10 MHz. However, itis understood that lower frequencies as well as frequencies of 100 MHzor even higher may be suitable for certain applications. In anillustrative embodiment, the range of frequencies is between 40 Hz and100 MHz. In a more particular illustrative process, the signals aregenerated at increments within the range of frequencies using alogarithmic sweep over the range of frequencies. The number ofincrements can vary, e.g., within a range between 50 to 250 increments.In a more particular embodiment, the total number of increments is in arange between 100 to 200. However, it is understood that these rangesfor the frequencies and increments are only illustrative. In otherembodiments, electrical signals of higher and/or lower frequencies canbe utilized and different amounts of increments, which can be uniform ornon-uniform throughout the range of frequencies can be used.

In action A18, the computer system 20 can measure a complex impedance ofthe soil 4 using the signal data acquired for the electrical signals ofmultiple frequencies. For example, the computer system 20 can use thevoltage magnitude and phase acquired for each frequency of electricalsignal to calculate a complex voltage for the frequency. The computersystem 20 can use the complex voltage to calculate the complex impedanceand a known measurement scheme (e.g., voltage divider).

In action A20, the computer system 20 can compute the complexpermittivity (e.g., effective permittivity) of the soil 4 using thecomplex impedance as well as an electrode model 36. The electrode model36 can be selected based on a particular configuration of electrodesused to acquire the data. For example, the electrode model 36 cancomprise a transmission line model. In an illustrative embodiment, thecomputer system 20 uses an electrode model 36 that is based on a coaxialtransmission line model for the electrode component 14 shown in FIGS. 2Aand 2B. For example, the model can include the formula:

$C = \frac{\pi\varepsilon}{ln\left( \frac{b}{a} \right)},$

where C is the capacitance of the soil, ε is the permittivity of thesoil, α is the radius of the wire (e.g., electrodes), and b is theradius between wires (e.g., between the conducting electrode 50 andprobe electrode 52). However, it is understood that a coaxialtransmission line model is only illustrative and other transmission linemodels, such as two-wire, planar, coplanar, etc., can be utilized.Adjustments to the model can be made based on the number of electrodesused in an active measurement (e.g., 2, 3, 4, or all 5) and theircorresponding lengths. In particular, as the number of electrodes andtheir corresponding configuration changes, the computer system 20 canadjust different values within the model. In an embodiment, theelectrode model 36 can further include a resistance-to-conductivityformula, which the computer system 20 can resolve to determineconductivity.

Regardless, the computer system 20 can use the electrode model 36 tocalculate the complex permittivity (or complex conductivity) of the soil4. For example, the measured complex impedance is dependent on aconfiguration of electrodes in the electrode component 14 and complexpermittivity (or complex conductivity) properties of the soil 4. Theelectrode model 36 is a mathematical representation of the configurationof electrodes in the electrode component 14. The computer system 20 canuse the electrode model 36 to remove an effect of the electrodeconfiguration from the complex impedance, which yields the complexpermittivity (or complex conductivity) properties of the soil 4.Therefore, other models can operate independently of the selectedelectrode configuration (setup). For example, if the electrodeconfiguration should need to be modified (e.g., to fit a certain fieldor a laboratory application), the electrode model changes can beincorporated without the need to adjust or make changes to other aspectsof the system (e.g., other models).

In an embodiment, the computer system 20 can measure a complexelectrical conductivity of the soil 4. For example, the computer system20 can determine the conductivity of the soil 4 by the phases (air,water, and solid particles) within a measured volume of the soil, whichcontribute to the measured conductivity. A measured effectiveconductivity of the soil 4 can be largely influenced by the watercontent and the conductivity of the soil solution (water), since boththe air and solid particle phases are non-conducting (σair = 0, σsolid =0). While air and solid particles are non-conducting, they can influencethe measurement due to their configuration (e.g., aggregation-porosity,connected pore space, structure, etc.) within the volume of soil 4.

In addition, the solid particles’ shape, orientation and sizedistribution, cation exchange capacity (CEC) and wettability affect theeffective conductivity. Tortuosity is used to describe the relationshipof the pore space (water and air phases) on the effective conductivitymeasurement and can affect the effective conductivity. Components of thesoil mixture, such as the specific surface area and particle shape,ionic strength and composition of the rock/soil contribute to themeasured conductivity. The computer system 20 can incorporate particleshape (e.g., spherical sand grains to needle-like clay tactoids) intothe effective conductivity modeling by using a depolarization factor,which describes the extent to which the inclusion of polarization isreduced according to its shape and orientation with respect to anapplied electrical field. While the factors affecting the effectiveconductivity of a soil mixture do not act separately, the geometricaland interfacial effects are greatly influenced by the water content.

In an embodiment, the computer system 20 uses a conductivity model tointerpret the measured signals. Illustrative conductivity models thatcan be used by the computer system 20 include: Archie’s law; mean fieldtheories (e.g., mixing formulas such as Maxwell formula/Maxwell-Garnettequation, Bruggeman’s model, coherent potential approximation, and auniversal mixing law), a self-similar model, which uses the effectivemedium theory (Maxwell-Garnett) and Archie’s law to model pore space;Hilhorst model; the effective conductivity as two conductors inparallel; a model based on the low-frequency polarization of the Stemlayer and the effect on the rest of the frequency data; methods/modelsthat use the Maxwell-Wagner polarization (e.g.,Maxwell-Wagner-Brugermann-Hanai (MWBH)); etc.

In an embodiment, the computer system 20 uses known information 39regarding the soil 4 in order to select a corresponding conductivitymodel. For example, the known information 39 can include one or moreknown and/or unknown conditions and/or properties of a desiredcharacteristic of the soil 4 to be determined. For example, the computersystem 20 can use Archie’s Law for soil 4 with low clay content and theself-similar model, due to its flexibility for simplification, when verylittle is known about the soil 4 and bulk properties of the soilsolution are desired. The computer system 20 also can use theself-similar model in instances when the soil 4 has a broad particlesize distribution, and thus a relatively low porosity and/or withnon-spherical particles by averaging the depolarization factor over allpossible particle orientations. The computer system 20 can obtain datacorresponding to the known and/or unknown conditions from a user 12and/or an external data source 33 using any solution.

In action A22, the computer system 20 can compute one or morecharacteristics of the soil 4 using the complex permittivity (or complexconductivity) and one or more mixing models 38. Illustrativecharacteristics of the soil 4 include the water content (e.g.,volumetric moisture content), a level of compaction (e.g., density),pore water conductivity, soil salinity, porosity, nitrate level, etc.Each mixing model 38 can correspond to one or more characteristics ofthe soil 4. The computer system 20 can use the mixing model 38 toestimate content from the measured permittivity of the soil 4. Dependingon the particular characteristic(s) to be computed, the computer system20 can use the corresponding mixing model(s) 38 that provide an estimatefor the characteristic(s). In an embodiment, the computer system 20 canuse known information 39 regarding the soil 4 to select from multiplepossible mixing models 38 for a particular characteristic. For example,the computer system 20 can use known data regarding the texture of thesoil 4 to obtain an initial estimate of the porosity of the soil. Theestimated porosity can be applied to a mixing model 38 to develop adensity estimate as porosity is dependent on both texture and density.

In an embodiment, one or more of the mixing models 38 comprises adielectric mixing model. In a more particular embodiment, the dielectricmixing model is similar to the Maxwell-Garnett (M-G) mixing model. TheM-G mixing model is based on the volumetric fractions of the componentswithin the volume of soil 4, not interaction effects between grains. TheM-G two-phase mixing model is:

$\varepsilon_{eff} = \varepsilon_{b} + 3f\varepsilon_{b}\left( \frac{\varepsilon_{1} - \varepsilon_{b}}{\varepsilon_{1} + 2\varepsilon_{b} - f\left( {\varepsilon_{1} - \varepsilon_{b}} \right)} \right),$

where ε_(b) is the permittivity of the background material (e.g., air,water, and/or the like), ε₁ is the permittivity solid inclusion, ƒ isthe volume faction of ε₁ and ƒ = 1 - Φ, Φ is the porosity of the soil,and ε_(eff) is the effective permittivity of the soil mixture. Thismacroscopic generalized mixing formula assumes the inclusion material isellipsoid in shape and the sizes of the inclusions in the mixture do notexceed a tenth of the wavelength in the effective medium.

However, it is understood that the M-G mixing model is only one type ofmixing model that can be utilized. For example, other mixing models canbe selected when the soil 4 has a high dielectric contrast ratio (e.g.,ε_(b) : ε₁), in which case the M-G mixing model has been shown to beless accurate. Other mixing models that use volume fractions andpermittivities include the Bruggeman model, and the Lichtenecker model.Another mixing model is a Maxwell-Wagner (MW) model, which models the MWeffect. The MW effect is an interfacial dispersion that occurs inmixtures with different permittivities. The MW effect typically occursin the kHz to MHz region and is strongly dependent on conductivity ofthe mixture, the water’s phase (bound or free water), and thetemperature.

In an embodiment, the computer system 20 uses a mixing model 38 thatdetermines the ionic concentrations of ions having differingconductivity at different frequencies from the conductivity measurementsacquired for different frequencies. The mixing model 38 can use weightedaverages of conductivities of the ions. For instance, assuming the soil4 contains strong electrolytes at a low concentration (c < 10 mM), thena molar conductivity follows Kohlrausch’s law,

$\text{Λ}_{m} = \text{Λ}_{m}^{0} - K\sqrt{c},$

such that K is an empirical constant that depends on the stoichiometryof the ions in solution, and

Λ_(m)⁰

is the limiting molar conductivity and is a known constant for commoninorganic ions, e.g.,

NO₃Λ_(m)⁰ = 71.4 cm²/mol.

The mixing model 38 can further use the Debye-Huckel-Onsager equation:

$\text{Λ}_{m} = \text{Λ}_{m}^{0} - \left( {A + B\text{Λ}_{m}^{0}} \right)\sqrt{c},$

where A and B are constants that depend on temperature, charges of ions,dielectric constant and viscosity of solvent. In an embodiment, thecomputer system 20 can use these equations along with the measured MWconductivity frequency response to isolate the types and concentrationsof different ions present in the soil 4.

In action A24, the computer system 20 can determine one or moreattribute levels in the soil 4 from the characteristic(s) of the soil 4.For example, the computer system 20 can determine a nitrate level in thesoil 4. In an embodiment, the computer system 20 uses a nonparametricBayesian inference approach to determine one or more of the attributelevels (e.g., the nitrate level) in the soil 4. A general Bayesianapproach has three components: the prior, the likelihood, and theposterior distributions. The prior can be described as what is knownabout the soil 4 before data is observed. The likelihood is the observeddata. The posterior is what is known after the data is observed (e.g.,nitrate level).

To this extent, the computer system 20 can implement a Bayesian solutionto calculate the nitrate level. The computer system 20 can interpretdata acquired for the soil 4 using the determined set of characteristics(e.g., water content, level of compaction, pore water conductivity,etc.) and additional known information 39 (e.g., priors) regarding thesoil 4 to aid in calculating the nitrate level. For example, such knowninformation 39 can include soil and environmental conditions.Illustrative known information 39 for the soil 4 can include amineralogy, texture (e.g., particle sizes) which can provide an estimatefor porosity, specific surface area, specific gravities of chiefmaterials, etc. Illustrative known information for the environmentalconditions include soil temperature, recent rainfall level, and/or thelike. The computer system 20 can obtain the known information 39 fromthe user 12 and/or an external data source 33 using any solution.Additionally, the computer system 20 can use the resulting posteriordistribution findings (e.g., previous nitrate prediction or a knownnitrate level) as a prior distribution in the next test of the soil 4.

Use of a Bayesian solution provides the computer system 20 withversatility in the nitrate model such that the posterior’s estimate ofthe nitrate level does not need to take a predetermined form. Instead,the computer system 20 can construct the estimate of the nitrate levelaccording to information derived from the data and known information 39.The Bayesian approach provides a framework for the computer system 20 toselect a model for the nitrate level and the nonparametric model allowsfor adaptation to changing data requirements. To this extent, thecomputer system 20 can adapt a complexity of the model (e.g., number ofdimensions) to the data and can grow the complexity of the model withdata size. In an embodiment, the computer system 20 can select a finitesubset of dimensions depending on the data and marginalize out theunneeded dimensions over the prior. In particular, the computer system20 can construct a likelihood function based on the observed field dataand the nonparametric model.

It is understood that the nitrate level is only an illustrativeattribute level in the soil that can be analyzed using a systemdescribed herein. Other illustrative attributes for which a level can bedetermined can include, without limitation, one or more of: potassium,phosphorous, calcium, magnesium, sodium, salinity, moisture, density,and/or the like. Additionally, embodiments can be utilized to analyzesoil directed to other applications including, without limitation, soilcontamination, quality control in food production, lawn care, and/or thelike.

The computer system 20 can store various data generated during theprocess described herein as medium data 34. For example, the medium data34 can include data corresponding to the characteristic(s) and/orattribute level(s) of the medium determined using the process describedherein. Additionally, the medium data 34 can include data correspondingto the test, such as a time stamp, geographic location, and/or the like,as well as some or all of the known information 39 used in analyzing themedium. Still further, the computer system 20 can store the raw signaldata acquired, data corresponding to a configuration of the electrodesused, data corresponding to the model(s) 36, 38 selected and used in thecalculations, a version number for the model(s) and/or algorithm used,and/or the like. In this manner, the computer system 20 can storesufficient medium data 34 to recreate the analysis and/or apply revisedanalysis for the soil 4.

In action A26, the computer system 20 can provide one or more of thedetermined characteristics, attribute levels, and/or the like, of thesoil 4 for use by the user 12. For example, the computer system 20 candisplay a density, moisture content, nitrate level, and/or the like, ofthe soil 4 as determined from the signal data. Additionally, thecomputer system 20 can transmit such data for use by another computersystem, such as a soil management system, which can initiate one or moreactions using the data (e.g., schedule an additional fertilization).Furthermore, the computer system 20 can store some or all of the data assoil data 34, which can be utilized as known information 39 for asubsequent evaluation of soil 4 for the same general location.

While shown and described herein primarily as a method and system foranalyzing soil, it is understood that aspects of the invention furtherprovide various alternative embodiments. For example, in one embodiment,the invention provides a computer program fixed in at least onecomputer-readable medium, which when executed, enables a computer systemto analyze a medium. To this extent, the computer-readable mediumincludes program code, such as the analysis program 30 (FIG. 1 ), whichenables a computer system to implement some or all of a processdescribed herein. It is understood that the term “computer-readablemedium” comprises one or more of any type of tangible medium ofexpression, now known or later developed, from which a copy of theprogram code can be perceived, reproduced, or otherwise communicated bya computing device. For example, the computer-readable medium cancomprise: one or more portable storage articles of manufacture; one ormore memory/storage components of a computing device; and/or the like.

In another embodiment, the invention provides a method of providing acopy of program code, such as the analysis program 30 (FIG. 1 ), whichenables a computer system to implement some or all of a processdescribed herein. In this case, a computer system can process a copy ofthe program code to generate and transmit, for reception at a second,distinct location, a set of data signals that has one or more of itscharacteristics set and/or changed in such a manner as to encode a copyof the program code in the set of data signals. Similarly, an embodimentof the invention provides a method of acquiring a copy of the programcode, which includes a computer system receiving the set of data signalsdescribed herein, and translating the set of data signals into a copy ofthe computer program fixed in at least one computer-readable medium. Ineither case, the set of data signals can be transmitted/received usingany type of communications link.

In still another embodiment, the invention provides a method ofgenerating a system for analyzing a medium. In this case, the generatingcan include configuring a computer system, such as the computer system20 (FIG. 1 ), to implement the method of analyzing a medium, such as asoil. The configuring can include obtaining (e.g., creating,maintaining, purchasing, modifying, using, making available, etc.) oneor more hardware components, with or without one or more softwaremodules, and setting up the components and/or modules to implement aprocess described herein. To this extent, the configuring can includedeploying one or more components to the computer system, which cancomprise one or more of: (1) installing program code on a computingdevice; (2) adding one or more computing and/or I/O devices to thecomputer system; (3) incorporating and/or modifying the computer systemto enable it to perform a process described herein; and/or the like.

It is understood that, unless otherwise specified, each value isapproximate and each range of values included herein is inclusive of theend values defining the range. As used herein, unless otherwise noted,the term “approximately” can be inclusive of values within +/- tenpercent of the stated value, while the term “substantially” can beinclusive of values within +/- five percent of the stated value.Furthermore, the phrase “in real time” means that the task is completedwithin a short time duration for a human user. In an illustrativeembodiment, “in real time” is inclusive of time periods less than tenminutes.

As used herein, unless otherwise noted, the term “set” means one or more(i.e., at least one) and the phrase “any solution” means any now knownor later developed solution. The singular forms “a,” “an,” and “the”include the plural forms as well, unless the context clearly indicatesotherwise. Additionally, the terms “comprises,” “includes,” “has,” andrelated forms of each, when used in this specification, specify thepresence of stated features, but do not preclude the presence oraddition of one or more other features and/or groups thereof.

The foregoing description of various aspects of the invention has beenpresented for purposes of illustration and description. It is notintended to be exhaustive or to limit the invention to the precise formdisclosed, and obviously, many modifications and variations arepossible. Such modifications and variations that may be apparent to anindividual in the art are included within the scope of the invention asdefined by the accompanying claims.

What is claimed is:
 1. A medium evaluation system, the systemcomprising: a computer system including a processor configured forevaluating a medium, the evaluating including the processor: determininga level of at least one attribute of the medium, using signal data forthe medium, the signal data including signal data acquired when each ofa plurality of electrical signals traveled through the medium, whereineach of the plurality of electrical signals has a different frequency ofa plurality of frequencies extending over a range of frequencies;wherein the determining includes computing a complex permittivity and/ora complex conductivity from the signal data; and wherein the determininguses a Bayesian inference solution to derive the level of at least oneattribute of the medium from the complex permittivity and/or the complexconductivity and known information regarding the medium.
 2. The systemof claim 1, further comprising an electrode component including aconducting electrode and a probe electrode, wherein the processor isfurther configured to operate the electrode component to emit, from theconducting electrode, each of the plurality of electrical signals intothe medium, and acquire, from the probe electrode, the signal data forthe medium.
 3. The system of claim 2, wherein the electrode componentfurther includes a template or guide that enables a user to insert theelectrodes into the medium at a known distance from each other.
 4. Thesystem of claim 3, wherein the template or guide enables selectiveinsertion of the electrodes at one of a plurality of known distances. 5.The system of claim 2, wherein the processor is further configured tospecify a configuration for placement of the electrodes in the mediumbased on the known information regarding the medium.
 6. The system ofclaim 2, wherein the probe electrode includes a pair of guard electrodeslocated on opposing sides of a guarded electrode to eliminate electricfield fringing effects at edges of the guarded electrode.
 7. The systemof claim 1, wherein the computing the complex permittivity and/or thecomplex conductivity includes: measuring a complex impedance of themedium using the signal data; and computing the complex permittivityand/or the complex conductivity, using the complex impedance and anelectrode model corresponding to a configuration of electrodes used toacquire the signal data, wherein the electrode model removes an effectof an arrangement for the configuration of electrodes used to acquirethe signal data from the complex impedance.
 8. The system of claim 1,wherein the known information regarding the medium includescharacteristics of the medium known from information available prior toeach of the plurality of electrical signals traveling through themedium.
 9. The system of claim 1, wherein the determining includes:computing a set of current characteristics of the medium using thecomplex permittivity and/or the complex conductivity; and determining alevel of at least one attribute of the soil using the Bayesian inferencesolution applied to the set of current characteristics and the knowninformation regarding the medium.
 10. A portable medium evaluationsystem, the system comprising: an electrode component including aconducting electrode and a probe electrode; and a computer systemincluding a processor configured for evaluating a medium, the evaluatingincluding the processor: operating the electrode component to emit, fromthe conducting electrode, each of a plurality of electrical signals intothe medium, wherein each of the plurality of electrical signals has adifferent frequency of a plurality of frequencies extending over a rangeof frequencies, and acquire, from the probe electrode, signal data forthe medium, wherein the signal data is acquired when each of theplurality of electrical signals travels through the medium; anddetermining a level of at least one attribute of the medium, using thesignal data for the medium. wherein the determining includes computing acomplex permittivity and/or a complex conductivity from the signal data,and wherein the determining uses a Bayesian inference solution to derivethe level of at least one attribute of the medium from the complexpermittivity and/or the complex conductivity and known informationregarding the medium.
 11. The system of claim 10, wherein the electrodecomponent further includes a template or guide that enables a user toinsert the electrodes into the medium at a known distance from eachother.
 12. The system of claim 11, wherein the template or guide enablesselective insertion of the electrodes at one of a plurality of knowndistances.
 13. The system of claim 10, wherein the processor is furtherconfigured to specify a configuration for placement of the electrodes inthe medium based on the known information regarding the medium.
 14. Thesystem of claim 10, wherein the probe electrode includes a pair of guardelectrodes located on opposing sides of a guarded electrode to eliminateelectric field fringing effects at edges of the guarded electrode. 15.The system of claim 10, wherein the medium is soil, and wherein theknown information includes a water content of the medium and the atleast one attribute level includes a nitrate level.
 16. A method ofevaluating a medium, the method comprising: a computer system computinga complex permittivity and/or a complex conductivity, using signal datafor the medium, the signal data including signal data acquired when eachof a plurality of electrical signals traveled through the medium,wherein each of the plurality of electrical signals has a differentfrequency of a plurality of frequencies extending over a range offrequencies; the computer system determining a level of at least oneattribute of the medium, wherein the determining includes the computersystem using a Bayesian inference solution to derive the level of atleast one attribute of the medium from the complex permittivity and/orthe complex conductivity and known information regarding the medium; andthe computer system providing the level of the at least one attribute ofthe medium for use in evaluating the medium.
 17. The method of claim 16,further comprising the computer system operating an electrode componentto emit, from a conducting electrode, each of the plurality ofelectrical signals into the medium, and acquire, from a probe electrode,the signal data for the medium.
 18. The method of claim 17, the computersystem specifying a configuration for placement of the electrodes in themedium based on the set of known characteristics of the medium.
 19. Themethod of claim 16, wherein the computer system computing the complexpermittivity and/or the complex conductivity includes: the computersystem measuring a complex impedance of the medium using the signaldata; and the computer system computing the complex permittivity and/ora complex conductivity, using the complex impedance and an electrodemodel corresponding to a configuration of the electrodes used to acquirethe signal data, wherein the electrode model removes an effect of anarrangement for the electrode configuration used to acquire the signaldata from the complex impedance.
 20. The method of claim 16, wherein thecomputer system determining the level of the at least one attribute ofthe medium includes: the computer system computing a set of currentcharacteristics of the medium using the complex permittivity and/or thecomplex conductivity; and the computer system determining the level ofthe at least one attribute of the soil using the Bayesian inferencesolution applied to the set of current characteristics and the knowninformation regarding the medium.